Attitude, knowledge and constraints associated with the climate smart agro-processing techniques in Sierra Leone

Abstract

This paper examines the attitude, knowledge, and constraints associated with climate-smart agro-processing techniques in Sierra Leone using binary logistic regression analysis. From a list of 150 agro-processors, a simple random sampling technique was used to select 134 processors. Data were collected through a structured questionnaire, which was face validated and demonstrated a reliability coefficient of 0.80. Data were analyzed using the Statistical Package for the Social Sciences (SPSS), Version 26, employing frequency counts, percentages, and binary logistic regression. Findings revealed that most agro-processors are male, young, with no formal education, and have from 5 to 10 years of operational experience. They exhibit low awareness and knowledge, but a favorable attitude toward climate-smart agro-processing techniques. Radio, workshops, and seminars were identified as the most common sources of information. The most popular processed products include rice and rice-based products (41.8%) and cassava-derived products (33.6%). Significant predictor variables for attitude toward climate-smart agro-processing techniques include: gender, age, education, business position, number of employees, years of operation, types of economic activities, market orientation, access to financial support, information sources, energy type, types of products, total by-products, and total number of agro-processing activities. Significant predictor variables for knowledge of climate-smart agro-processing techniques include: total by-product management, APCST constraints, APCST awareness, and APCST use. These significant predictors highlight key intervention areas necessary for effective application of agro-processing techniques aimed at promoting climate adaptation and mitigation.